Andreas S. Weigend, Ph.D. - Data Mining and E-Business - Stanford University Interview





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Uploaded on Apr 16, 2009

http://www.weigend.com - Andreas Weigend is a former Chief Scientist at Amazon.com and the author of over 100 scientific papers on the application of machine learning techniques to finance and business problems.

He currently lectures at Stanford, Berkeley and Tsinghua Universities on the application of data analysis to electronic business problems. He is an advisor to many technology companies including MySpace and Nokia, and is a limited partner in The Founders Fund.

Data Mining and Electronic Business: The Social Data Revolution
Extract Insights from Twitter
Put Yourself in Google's Shoes
Develop Relevance Beyond Amazon
Help Skout.com Improve your Love Life
Build Revolutionary Facebook Applications

In the last year, your location data and personal medical information have become the latest streams in the river of data, joining email, clicks, searches, social networking, and buying patterns. This course will dramatically change how you think about your data.

How can these data sources make our lives easier, more effective, more interesting? How can we get better recommendations, based on our behavior and the behavior of our friends? How can reputation systems help with decisions about who to trust?

Gathering, sharing, and storing data has become trivial. But what shall we collect, and what applications can we build that users really want?

Moving beyond graph and guess, push and pray, launch and learn, and so on, this course gives you tools and strategies for successful applications. How can you optimize virality and engagement, and spot weaknesses early? How can you entice users to interact with the app, and recommend it to their friends?

Each class is structured according to PHAME: define relevant Problems, invent Hypotheses, create Actions, design Metrics, and conduct Experiments. We also introduce a key driver to encourage users to provide critical data: Return on Personal Engagement (ROPE). Users who gain a benefit (tangible or psychological) from participating are far more likely to do so, and we discuss how to design incentives to encourage participation.

Course time is enriched by notable speakers, from notable companies. In addition to discussing applications that succeeded, we also discuss applications that failed, and try to distill out the reasons for success and failure. This course also includes highlights from two courses I developed and taught at Berkeley last year, including the popular"Marketing 2.x" at the Haas School of Business.

Data mining is no longer the process of digging through data morgues to uncover scraps of still-viable information. Success in the online marketplace now hinges on people and the data they create. E-business is no longer about selling books.

Secondary video edits (this current YouTube version; including intro, outro & textual content) produced by Shaun Tai for SHAUN TAI Films / TECH AFFAIR (www.techaffair.com) - ©2009 - shaun@ztymedia.com, (925) 297-9370.

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